• PhD Candidate
  • Department of Political Science
  • Social & Behavioral Science Building, 7th floor
  • Stony Brook University
  • Stony Brook NY 11794-4392
  • james.cragun [[ at ]] stonybrook . edu

Research Interests

Motivated reasoning, selective exposure, misinformation, judgment & decision making, cognitive biases, scientific and economic reasoning, personality & individual differences, religious cognition, evolutionary psychology, public choice, electoral systems, quantitative methods, agent-based models and computer simulations, pedagogy


Dissertation Research

Individual Differences in Motivated Reasoning and Selective Exposure
Broadly I am interested in how people seek and process information when forming political opinions. It is already widely understood that people are motivated to maintain and support their prior beliefs and attitudes and that people tend to seek information that will support their prior beliefs and attitudes rather than information that will challenge them. I am interested in discovering which individuals do so to a greater extent than others and what variables in a person’s life can affect the development of such individual differences.

Working paper: "Intuition and Reflection as Sources of Individual Differences in Selective Exposure", Appendix

Working paper: "Religious Faith Promotes Selective Exposure to Attitude-Congruent Political Information"

Current project (at the data-analysis stage): "How Do You Make an Open-Minded Person? The Effect of Social Environment Heterogeneity Among Residents of Student Housing on Selective Exposure in Political Information Seeking"


Observational results: Religious faith and selective exposure


Experimental results: Religious faith and selective exposure


Other current projects

Evolution of One-Shot Cooperation Under Uncertainty: An Agent-Based Model
Cooperation for mutual benefit is a fundamental aspect of politics, and behavioral economics research has provided much knowledge about the degree to which humans tend to cooperate and the conditions under which they do so. Although it is often not optimal, from a traditional economic (rational egoist) perspective, to cooperate when in a one-shot (non-repeated) interaction, experimental research has shown that many individuals do cooperate even in one-shot interactions. This may be because the typical experimental situation in which subjects are told with certainty that they are in a one-shot interaction is unlike the situations humans often encounter in real life. In real interactions, an individual would have a belief about whether the current interaction is a one-shot or repeated interaction, but those beliefs could sometimes be wrong. The opportunity cost of failing to cooperate when an interaction turns out to be a repeated interaction may be greater than the cost of cooperating when an interaction turns out to be a one-shot interaction, so a tendency to cooperate even when the individual believes the interaction is more likely to be a one-shot interaction could be beneficial in the long run. I have created a computer simulation showing the evolution of this behavioral trait. Over thousands of generations of simulated agents interacting with each other, producing offspring in proportion to their level of success in those interactions, and passing their behavioral tendencies to their offspring, the tendency to cooperate even when they believe a one-shot interaction is more likely becomes common in the population. This model is based on a model previously published by Delton et al (2011) but includes some important modifications. A paper will be produced soon, but some preliminary results can be seen in these rough slides from a short presentation I gave on the project.
Presentation slides: Evolution of One-Shot Cooperation

Frequency of Opportunities for Strategic Voting Under Different Voting Systems: A Computational Simulation
I simulate spatial policy positions of a set of three or more candidates and ideal points of a set of voters, generating a preferences of each voter over the set of candidates. For several different single-winner electoral rules, including the standard single-vote plurality rule, approval voting, and ranked-choice ballots with single transferable vote, I specify each voter's non-strategic vote based on their preferences and I determine the election winner under the non-strategic voting profile. I then test every possible deviation of each voter from that non-strategic voting profile to determine whether any voter can obtain a better by voting strategically. I then repeat the process hundreds of times, randomly drawing a new distribution of candidate and voter positions for each new simulation, and I calculate the proportion of simulations in which an opportunity for strategic voting exists under each voting rule and under varying quantities of candidates and varying quantities of voters.

Pedagogical research: teaching critical reasoning skills
I am working with Peter Liberman of the City University of New York (CUNY), who is developing a new reasoning-training method for students of introductory political science courses. The new teaching method, which involves computer-based argument-mapping puzzles, will be implemented in undergraduate courses using multiple treatment and control groups, and then various learning outcomes will be measured at the end of the semester, including logical reasoning skills, ability to evaluate arguments in an unbiased manner, open-mindedness, and willingness to seek challenging information when forming opinions.